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An intelligent interactive system based on LLM to combine CAD API development with FEA 8

An intelligent interactive system based on LLM to combine CA...

引用

8th international conference on Electrical, Mechanical and computer engineering, ICEMCE 2024

作者： Yu, Mengqiang Sheng, Yujie Wan, Zhongxu Yang, Shuyu Sun, Muping Cai, Hongxia Shanghai University School of Mechatronic Engineering and Automation Shanghai China Shanghai University Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai China Shanghai University School of Communication and Information Engineering Shanghai China

ISBN: (纸本)9798331506230

This paper presents an intelligent interactive system based on large language model (LLM). It aims to simplify the operation flow of CAD and FEA software and improve the efficiency of design and simulation analysis. The system uses C# and Python to develop CAD Secondarily and access LLM API locally. Build a professional database and implement the interaction between CAD and LLM. The natural language dialogue between the user and the CAD software is realized, and the design guidance and optimization suggestions are provided. Taking the design of the end mechanism of fruit picking robot as an example, the application effect of this system is demonstrated. The results of the case show that the system can effectively improve the efficiency of design and simulation analysis, and improve the design quality, and has a broad application prospect. © 2024 IEEE.

关键词： Machine design

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Wheat Breeding Across the Full Lifecycle with Multimodal Deep Learning: Practical Review and Future Strategies 2

Wheat Breeding Across the Full Lifecycle with Multimodal Dee...

引用

2nd international conference on Artificial Intelligence and automation Control, AIAC 2024

作者： Zhang, Lei Li, Xueyong Xinxiang University Department of Computer and Information Engineering Xinxiang China College of Computer and Artificial Intelligence Wuhan University of Technology Wuhan China Henan University of Science and Technology Department of Computer Science and Technology Xinxiang China

ISBN: (纸本)9798331529147

This review explores the use of multimodal deep learning in wheat breeding to tackle issues like extended cycles, inefficiency, and environmental adaptability. It integrates diverse data and deep learning to monitor wheat's growth, stress resistance, and yield. The study employs models like LSTM, ResNet50, and GNN to extract phenotypic features, creating a new approach to full lifecycle breeding. A multimodal dataset with hyperspectral and RGB images and genotypic data is used to extract features, ensuring data analysis accuracy. The research also includes stress resistance analysis and genotypic association mining to develop precise breeding strategies. A data platform is built for efficient data storage, analysis, and sharing in wheat breeding. The study supports the advancement of smart agriculture through multimodal deep learning, enabling monitoring and precise breeding across wheat's growth. Future work will optimize algorithms, datasets, and model generalization for broader application in wheat breeding. © 2024 IEEE.

关键词： Data accuracy

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Design and implementation of urban rail vehicle ATC digital debugging system 3

Design and implementation of urban rail vehicle ATC digital ...

引用

3rd international conference on Electronic Information engineering, Big Data, and computer Technology, EIBDCT 2024

作者： Yang, Shuo Zhang, Chunguang Zhang, Lifang School of Automation and Electrical Engineering Dalian Jiaotong University Dalian China

ISBN: (纸本)9781510680449

In order to solve the problems of cumbersome operation steps in the current static debugging of subway ATC equipment and error-prone manual recording and judgment of test data, a subway simulated ATC intelligent equipment system base d on MQTT protocol is designed and developed to improve the debugging efficiency and security. By configuring MQTT connection IP parameters and establishing MQTT connection, the intelligent equipment can release the working status a nd test results in real time. The Spring Boot and Vue framework monitoring system is built through the cloud server and used to subscribe and monitor the status information of the intelligent equipment, so as to realize the information management of the whole process of vehicle debugging. The design scheme improves the efficiency and security of subway ATC equipment debugging and meets the basic requirements of constructing digital debugging production line. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Efficiency

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An IoT-Based Sustainable automation System for the Garments Industry in Bangladesh 3

An IoT-Based Sustainable Automation System for the Garments ...

引用

3rd international conference on Emerging Frontiers in Electrical and Electronic Technologies, ICEFEET 2023

作者： Ahmed, Khandakar Rabbi Salam, Towfika Rabbu, Mohammad Mahmudul Haque, F.M. Hasan, Nazmul Miraz, Shafiun Rana, Md. Masud Mansur, Maliha Tabassum, Humayra Shayer, Khandokar Shadman Miyan Research Institute International University of Business Agriculture and Technology Dhaka Bangladesh Dept. of Mechatronics Engineering Rajshahi6204 Bangladesh International University of Business Agriculture and Technology Dept. of Computer Science and Engineering Dhaka Bangladesh Ahsanullah University of Science and Technology Dept. of Computer Science & Engineering Dhaka Bangladesh Ahsanullah University of Science and Technology Dept. of Electrical & Electronic Engineering Dhaka Bangladesh Varendra University Dept. of Computer Science and Engineering Rajshahi Bangladesh Dept. of Computer Science and Engineering Rajshahi Bangladesh Ahsanullah University of Science & Technology-Bangladesh Dept. of Electrical & Electronic Engineering Dhaka Bangladesh American International University-Bangladesh Dept. of Electrical & Electronic Engineering Dhaka Bangladesh

ISBN: (纸本)9798350307399

The Readymade Garments sector accelerates Bangladesh's development. The 'Made in Bangladesh' brand has also helped to boost Bangladesh's reputation and brand recognition on a global scale. Despite its limited resources, the country has maintained a 6% annual GDP growth rate while attaining extraordinary social and human development. On the other hand, the phrase 'Internet of Things' (IoT) refers to a broad concept that can be summarized as an ecosystem of intelligent gadgets equipped with networks, sensors, and processing tools. IoT is a new technological platform that enables the many objects in our environment to connect via sensors and the Internet to improve our quality of life. Manufacturing and the industrial sector, agriculture, the health sector, smart cities, security, and emergency services, to name a few. IoT implementation in the garment sector would open a new door to growth in production and worker safety. Implementing home automation and safety systems in the garment sector will help in production and ensure the safety of the workers. The suggested IoT -based sustainable automation system for the Bangladeshi garments sector is efficient, eco-friendly, secure, reliable, and user-friendly. The system's user-friendly interface makes it straightforward to use and manage. The Bangladeshi garments industry's IoT -based sustainable automation system is a comprehensive and integrated solution that addresses the industry's primary difficulties and provides a sustainable and viable future. © 2023 IEEE.

关键词： Internet of things

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Real-time heat sealing quality analysis of film based on digital twin system 3

Real-time heat sealing quality analysis of film based on dig...

引用

3rd international conference on Electronic Information engineering, Big Data, and computer Technology, EIBDCT 2024

作者： Zhao, Jun Shen, Nanyan Li, Jing Li, Yufei Li, Haoyang School of Mechatronic Engineering and Automation Shanghai University Shanghai Baoshan China

ISBN: (纸本)9781510680449

Digital twin achieves interactive mapping between physical entities and virtual models, enabling continuous real-time monitoring of process quality in virtual spaces. This paper addresses the issues of high latency and poor correlation with heat sealing process parameters in the quality inspection of plastic film heat sealing, and explores real-time analysis of heat sealing quality based on digital twin technology. The focus is on the finite element analysis of typical heat sealing process parameters combined with thermo-structural coupling, boundary condition modification and data-driven modeling. The study reveals the relationship between controllable heat sealing process parameters and film heat sealing quality, achieving real-time monitoring of the heat sealing quality of plastic sealing film © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Quality control

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Sign to Text: Automated Sign Language Interpretation using LSTM and computer Vision 3

Sign to Text: Automated Sign Language Interpretation using L...

引用

3rd international conference on automation, Computing and Renewable Systems, ICACRS 2024

作者： Sankara Mahalingam, M. Suresh Kumar, N. Harika, Chintapudi Harika, Chennamsetty Reddy, Chintala Sankar Kalyan, Dasari Pavan Department of Computer Science and Engineering Kalasalingam Academy of Research and Education Tamilnadu Virudhnagar India

ISBN: (纸本)9798331532420

Sign language serves as a crucial communication tool for individuals with speech or hearing impairments. Recent advancements in computer vision and deep learning offer opportunities to develop efficient, real-time sign language recognition systems that bridge communication gaps. This study proposes a sign language recognition model utilizing the Mediapipe model and Long Short-Term Memory (LSTM) networks to detect and interpret American Sign Language (ASL) gestures in real time. The proposed system extracts and analyzes key landmarks across the body, hands, and face, leveraging CNN-LSTM architecture to capture both spatial and temporal features essential for accurate gesture recognition. Evaluated on a diverse ASL dataset, the proposed model achieved an accuracy of 92%, demonstrating robustness and adaptability in varied environments. The proposed approach holds promise for applications in assistive technologies and educational tools, providing an accessible solution for sign language interpretation. © 2024 IEEE.

关键词： Long short-term memory

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Fault Correlation Analysis Algorithm for Multi-Satellite Telemetry Data Based on State Transition Relationships 2

Fault Correlation Analysis Algorithm for Multi-Satellite Tel...

引用

2nd IEEE international conference on Electrical, automation and computer engineering, ICEACE 2024

作者： Qi, Xinhu Sun, Darui Chen, Haoyi Song, Nan Chen, Yanbin Zhang, Yanning Northwestern Polytechnical University School of Computer Science Xi'an710072 China Space Star Technology Co. Ltd. Beijing100095 China

ISBN: (纸本)9798350368208

In the operational phase of satellites, a substantial amount of telemetry parameters related to physical and state changes are generated, complicating the correlation analysis of faults. This challenge is particularly pronounced in the absence of historical contingency plans, making it difficult to pinpoint relevant telemetry parameters following fault occurrences. This paper presents an algorithm designed for multi-satellite telemetry that conducts correlation analysis of telemetry parameters leading to fault events. The proposed algorithm facilitates multi-satellite telemetry data analysis, establishes strong correlations between fault occurrences and telemetry parameters, and provides interpretable functionalities. Initially, the algorithm conducts state analysis based on actual satellite telemetry data to examine the changes in telemetry parameters. This analysis serves as the foundation for feature encoding, which describes the variations of telemetry parameters within a temporal motion context. Finally, the algorithm employs feature importance analysis within a Random Forest framework to identify telemetry parameters that exhibit a strong correlation with the fault occurrence. This algorithm was applied in a real-world fault scenario in the aerospace domain. The results of telemetry parameters obtained by the algorithm have a strong correlation with the fault occurrence, and have a high consistency with the results inferred by the diagnosis experts. © 2024 IEEE.

关键词： Decision trees

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Calculation of polygon-based holograms for textured surfaces using orthogonal projection 3

Calculation of polygon-based holograms for textured surfaces...

引用

3rd international conference on Electronic Information engineering, Big Data, and computer Technology, EIBDCT 2024

作者： Wu, Jun Hao, Shaowen Kang, Jiachen School of Electronic Engineering and Automation Guilin University of Electronic Technology Guilin541000 China

ISBN: (纸本)9781510680449

In the current landscape of technological advancements, holography is acknowledged as one of the most promising three-dimensional display technologies. To enhance the quality of holographic reproductions and address the issue of texture mapping distortion, this paper proposes an innovative method based on orthogonal texture mapping for generating three-dimensional model-computed holograms. This approach leverages the analytical polygonal element method, incorporates the Blinn-Phong reflection model to acquire lighting information, and employs orthogonal projection for obtaining texture information. The result is the generation of high-quality three-dimensional object-computed holograms. Numerical simulation experiments demonstrate that the holographic reconstructions generated by our method exhibit undistorted and non-distorted textures on the surface, presenting superior visual quality. This method holds significant theoretical and practical value. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Holograms

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Interpretable Software Maintenance and Support Effort Prediction Using Machine Learning 24

Interpretable Software Maintenance and Support Effort Predic...

引用

46th international conference on Software engineering: Companion, ICSE-Companion 2024

作者： Haldar, Susmita Capretz, Luiz Fernando School of Information Technology Fanshawe College LondonON Canada Department of Electrical and Computer Engineering Western University LondonON Canada

ISBN: (纸本)9798400705021

Software maintenance and support efforts consume a significant amount of the software project budget to operate the software system in its expected quality. Manually estimating the total hours required for this phase can be very time-consuming, and often differs from the actual cost that is incurred. The automation of these estimation processes can be implemented with the aid of machine learning algorithms. The maintenance and support effort prediction models need to be explainable so that project managers can understand which features contributed to the model outcome. This study contributes to the development of the maintenance and support effort prediction model using various tree-based regression machine-learning techniques from cross-company project information. The developed models were explained using the stateof- the-art model agnostic technique SHapley Additive Explanations (SHAP) to understand the significance of features from the developed model. This study concluded that staff size, application size, and number of defects are major contributors to the maintenance and support effort prediction models. © 2024 IEEE computer Society. All rights reserved.

关键词： Forecasting

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A Comprehensive Framework for Video Resolution Enhancement: Using computer Vision and Deep Learning Techniques 8

A Comprehensive Framework for Video Resolution Enhancement: ...

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8th IEEE international conference on Computing, Communication, Control and automation, ICCUBEA 2024

作者： Pathak, Bageshree Bidada, Tejal Manakapure, Rutuja Pawar, Harsha Jakhalekar, Tanvi MKSSS's Cummins College of Engineering for Women Department of Electronics and Telecommunication Pune India

ISBN: (纸本)9798350391770

The paper introduces a computer vision based four-phase framework for enhancing video resolution by removing motion blur and motion based temporal aliasing. Beginning with stabilization using the Lucas-Kanade method, a stable foundation is created. Subsequent stages involve deblurring through Gaussian blurring and Wiener deblurring, addressing temporal aliasing with bicubic interpolation. To further boost resolution a final denoising stage using Non-Local Means method reduces noise while preserving details in a video. To overcome the limitations of computer vision based model we have designed a deep learning approach with the U-Net architecture employed for large motion frame interpolation. U-Net enhances spatial features and even uses Super Resolution Convolutional Neural Network (SRCNN) for deblurring of video and making the video more sharper. This innovative methodology aims to redefine video resolution, with potential applications in surveillance, video analytics and content creation. © 2024 IEEE.

关键词： Convolutional neural networks

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